Respiratory rate (RR) as referred to as breathing rate, is an indicator of patient health with particular relevance to respiratory and cardiovascular functions. Respiratory rate exceeding 27 breaths per minute has been found to be the most important predictor of cardiac arrests in hospital wards. In another study it was found that more than 50% of the patients suffering an adverse event in a hospital had a respiratory rate greater than 24 breaths per minute up to 24 hours before the event. In spite of this, respiration rate is often a neglected vital sign not routinely measured in clinical practice. One reason for this is that the manual measurement of respiration rate (counting breaths at the patient bedside) is a cumbersome process. Furthermore, measurement of respiration rate does not yield continuous estimates of respiration rate and has a high likelihood of missing important respiration events during the unmonitored period. In addition, methods for unobtrusive continuous respiration rate estimation using, for example, impedance Plethysmography (IP), have poor measurement accuracy owed largely to algorithmic insufficiency.
In the absence of a reliable respiration rate measure, a patient's peripheral oxygen saturation (SpO2) estimates are utilized as a parameter to detect stress, as indicated when SpO2 values drop below a preset threshold (usually 85-90%). The SpO2 estimates, however, are a very late indicator of patient distress since any lack of oxygenation is often compensated by an increased ventilation drive. When the SpO2 reading drops below the preset threshold, patient status is already severely deteriorated. Therefore, SpO2 alone is not sufficient to detect patient distress.
Rather, trends in respiration rate and SpO2 offer insight into patient status such as the indicated three patterns of patient distress (patterns in SpO2 and RR), noted as the most likely to be encountered in a hospital environment. Three characteristic multi-parametric trend patterns named as Type I, II and III (FIG. 1, PRIOR ART) are explained as:
Type I (FIG. 1A): Hyperventilation Compensated Respiratory Distress (e.g. Sepsis, PE, CHF)—A patient has a gradual decrease in SpO2 with compensatory hyperventilation.
Type II (FIG. 1B): Progressive unidirectional hypoventilation—A patient has a progressive fall in minute ventilation (Ve: Volume inhaled or exhaled from a person's lungs per minute) and SpO2 most often brought about my narcotic (sedative) overdose.
Type III (FIG. 1C): Sentinel rapid airflow/SpO2 reductions followed by precipitous SpO2 fall—This type of pattern is most often noted in patients with sleep apnea wherein breathing is characterized by alternating patterns of hyperventilation and no breath. Death in most instances is a result of arousal failure after a prolonged apnea.
As shown in FIG. 1, SpO2 is a late indicator of an adverse event. By the time SpO2 starts to rapidly decline, the patient is in distress: The PACO2 has been declining and RR and Ve have been increasing. Hospitals fail to recognize the patterns as referenced, as well as lack the systems to identify or characterize these patterns. Current hospital monitoring also fails to identify these trends during vital sign collection and fails to offer detection systems or processing that have the capability to analyze data and deliver an output to realize early patient distress. A multitude of false alarms further inhibits care at the patient's bedside in most urgent situations, increasing the risk for a critical care patient and inhibiting prioritized response of one patient's critical state as compared to another. When an alarm goes off, a silence action is implemented by a clinician or after a time delay. The increase in alarm systems at the bedside has led to increased silencing as the alarms have become monotonous and overused. Thus, this leads to mistakenly silencing critical events.
The invention disclosed in the following addresses the issues as indicated above and further resolves the need for clinical systems that currently lack the monitoring and analytical capabilities that would prevent false alarm fatigue and alert providers earlier as to deteriorating patient condition.